The MACS, a large comprehensive cohort study of gay men, has made important contributions to the epidemiology and natural history of HIV infection and AIDS. With the introduction of potent anti-retroviral therapies, there are scientific issues of great significance that necessitate the continuation of this cohort. The 4 sites and the data center have collaborated productively since 1983. After 15 years, 75% of the living participants have been retained in active follow-up. It is estimated that by the year 2003, there will be 657 AIDS-free HIV positive and 116 AIDS cases under follow-up. These men and selected subsets of the persistently seronegative cohort members will provide data to achieve the scientific goals of the MACS, which are to define: 1) effectiveness of therapies at the population level; 2) determinants of use and response to therapies; 3) virologic characteristics, immune responses and genetics of progressors and long-term non-progressors; 4) mechanisms of resistance to infection; 5) prognostic markers in treated individuals; 6) determinants of specific clinical outcomes; and 7) epidemiology of HIV-1 related malignancies. Part A of this proposal describes the study's core methods which will be implemented by MACS investigations in collaboration with the MACS Pathogenesis Research Laboratories (MPRL) and external investigators. Part B of this proposal contains details of the application of the Center for the Coordination, Analysis and Management of the MACS research (CAMACS). The specific aims of CAMACS are: 1) to coordinate the MACS-wide research including the MPRL; 2) to manage the data collected, including repository samples; 3) to collaborate in the design and analysis of pathogenesis studies; 4) to provide leadership in analysis and interpretation of MACS-wide data, including methodological research; and 5) to issue a MACS public data base for external investigators. CAMACS investigators have expertise in research coordination, systems and data management, epidemiology and biostatistical methods for complex longitudinal data and survival analysis.